Software Engineer, Customer Studio Backend

Job Description

Job Description

Software Engineer, Customer Studio Backend (Senior)

Location: Remote (North America)
Compensation: $180,000–$320,000 base (location-independent) + meaningful equity (ISO options; early exercise + 10-year post-termination window)

About Our Client

Our client is an AI platform for marketing and growth teams. Their AI agents reimagine marketing workflows—helping teams create content, plan campaigns, build audiences, and execute strategies with significantly higher velocity and performance.

They sit at the intersection of two major tailwinds: agentic AI/LLMs and the widespread adoption of cloud data warehouses (e.g., Snowflake and Databricks). The platform is trusted by leading brands and high-growth companies across consumer and B2B.

Culturally, they value first-principles thinking, speed with discipline, strong communication, and a team environment rooted in kindness and ownership.

About the Team / Product

Customer Studio is our client's second major product: a purpose-built no-code suite that enables teams to activate data directly from their data warehouse—no SQL required. It's become core to how marketing and growth teams build audiences, measure performance, and run campaigns. It also serves as underlying infrastructure that powers agentic marketing workflows.

This team blends product and customer-first thinking with challenges at high data scale , pushing what warehouses can do in terms of speed, interactivity, and reliability.

The Role

Our client is hiring a product-minded backend engineer to help scale Customer Studio. You'll go deep on backend and distributed systems while thinking holistically about architecture, scalability, maintainability, and reliability. You'll also be comfortable engaging with product specs—writing them when needed and partnering closely with product stakeholders.

This is considered a senior role, but the company prioritizes impact and growth potential over a specific number of years.

What You'll Work On

• Data Warehouse Performance: Push the limits of speed and interactivity by optimizing queries, leveraging pre-computed state, and implementing warehouse-specific improvements
• Analytics & Experimentation: Help customers build segments and decide what data to sync; enable experimentation workflows and track audience performance downstream
• Real-Time Audience Syncing: Explore fresher, faster syncing as warehouses adopt more real-time patterns (including CDC)
• Generative AI Enhancements: Improve the user experience of acting on data using AI to reduce friction and increase automation

What Our Client Is Looking For

• Strong backend engineering fundamentals with experience building scalable, reliable systems
• Comfort with distributed systems concepts and architectural tradeoffs
• Product and customer thinking: you care about usability, workflows, and outcomes—not just backend correctness
• Ability to write and collaborate on product specs and communicate clearly with cross-functional partners
• High standards for maintainability, reliability, and operational excellence
• Intellectual curiosity and a bias toward execution

Bonus signals (not required): experience with cloud data warehouses, query optimization, event-driven systems, CDC/streaming patterns, or building data products for marketing/growth teams.

Compensation & Equity

• Base salary: $180,000–$320,000 USD (location-independent within NA)
• Meaningful equity via ISO options (includes early exercise and a 10-year post-termination exercise window)

Interview Process

This process is designed to evaluate product sense, backend/distributed system architecture, and values alignment—without programming interviews.

1. Recruiter Screen (30 min): Intro call to assess mutual fit
2. System Design Screen (45 min): Design a data processing feature end-to-end
3. Hiring Manager Interview (30 min): Past experience + operating preferences + values alignment
4. System Design Interview (90 min): Architect a high-level system with product/customer requirements and technical constraints